scout

Identify uncertainties in research framing, datasets, metrics, and baselines.

Updated Apr 16, 2026
One-click install
npx skills add https://github.com/yu13130122297/helloCat --skill scout-yu13130122297
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: scout
Source: https://github.com/yu13130122297/helloCat/tree/main/src/skills/scout
Command: npx skills add https://github.com/yu13130122297/helloCat --skill scout-yu13130122297

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and scripts (resource) and assets (resource) components.

What problem does it solve?

Facilitates initial problem definition by clarifying task scope, data, metrics, and existing baselines, enabling more efficient research progression.

Core Features & Use Cases

  • Task Framing: Assists in defining precise research questions when the objective is ambiguous.
  • Literature and Repo Discovery: Helps identify relevant papers and repositories to establish context and baseline options.
  • Evaluation Setup: Clarifies dataset and metric contracts to synchronize understanding before experimentation.
  • Baseline Identification: Guides the selection and shortlisting of foundational methods for comparison.
  • Use Case: A researcher resuming work on an open problem needs to understand existing approaches and define clear evaluation criteria; scout provides structured insights for next steps.

Quick Start

Ask the AI to identify the task, datasets, metrics, and existing baselines to prepare for experiments.

Frequently Asked Questions about scout

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I clarify research problem framing and dataset scope for early-stage experiments?

To clarify research problem framing and dataset scope, identify uncertainties in task definition, data boundaries, evaluation metrics, and baseline options to establish a clear research direction and define actionable next steps.

What is the best way to discover relevant literature and baseline repositories for a new research task?

The best way to discover relevant literature and baseline repositories is to scout existing approaches, identify relevant papers, and shortlist foundational methods to establish context and comparison options for your research progression.

How do I set up evaluation metrics and dataset contracts before starting model experimentation?

To set up evaluation metrics and dataset contracts, clarify the dataset scope and metric definitions to synchronize understanding, ensuring clear evaluation criteria are established before you begin actual experimentation.

Can I use literature scouting to define actionable next steps when resuming an open research problem?

Yes, you can use literature scouting to define actionable next steps by understanding existing approaches, identifying task framing uncertainties, and shortlisting baselines to prepare structured insights for your experiments.

When do I need early-stage quest framing for my research progression?

You need early-stage quest framing when your research objective is ambiguous, requiring you to define precise research questions, clarify task scope, and identify existing baselines to enable more efficient research progression.